Background Adaptive Division Filtering for Hand-held Ground Penetrating Radar
Lee, M., Anderson, D., Ball, J. E., & White, J. (2016). Background Adaptive Division Filtering for Hand-held Ground Penetrating Radar. SPIE. Baltimore, MD: SPIE Defence and Security.
Buried explosive hazards are a serious threat to both civilians and soldiers in current and former conflict zones. Herein, we focus on handheld downward looking ground penetrating radar. The signal enhancement algorithm explored is motivated by deconvolution. We discuss global, local and adaptive estimation implementations of the core algorithm. Furthermore, we investigate the additional enhancement of the signal in post-processing using Curvelets. Both qualitative and quantitative results, in the context of ROC curves, are demonstrated on data from a U.S. Army test site that contains multiple target and clutter types.